BluePes Blog: Insights & Trends

What Types of Tasks Can Be Solved with Data Science?

Data scientists work with different business needs to discover insights from existing data. There is no single technology that encompasses data science. Different tasks require different technologies, and, very often, several of them. In this article, we discuss the main tasks facing data scientists when solving problems for businesses.

• Mykola Lavrskyi
• Jul 02, 2019
• 9 min

Real Life Data Science Applications in Healthcare

Due to healthcare's importance to humanity and the amount of money concentrated in the industry, its representatives were among the first to see the immense benefits to be gained from innovative data science solutions. For healthcare providers, it’s not just about lower costs and faster decisions. Data science also helps provide better services to patients and makes doctors' work easier. But that’s theory, and today we’re looking at specifics.

• Mykola Lavrskyi
• May 21, 2019
• 5 min

A Brief History of Data Science

Data science, AI, and Big Data have been the biggest buzzwords of the technological world over recent years. But even though there’s a lot of marketing fluff involved, these technologies do make a real difference in highly complex industries like healthcare, financial trading, travel, energy management, social media, fraud detection, image and speech recognition, etc. With the digitalization of the world economy and virtually every aspect of life, data has become the new oil (a term coined by Clive Humby). Subsequently, data science has become the sexiest job of the 21st century. But that’s really cutting a long story too short. Let’s look at the development of data science in more detail.

• Mykola Lavrskyi
• May 06, 2019
• 5 min

What is Data Science?

In recent years, data science has become increasingly prominent in the common consciousness. Since 2010, its popularity as a field has exploded. Between 2010 and 2012, the number of data scientist job postings increased by 15 000%. In terms of education, there are now academic programs that train specialists in data science. You can even complete a PhD degree in this field of study. Dozens of conferences are held annually on the topics of data science, big data and AI. There are several contributing factors to the growing level of interest in this field, namely: 1. The need to analyze a growing volume of data collected by corporations and governments 2. Price reductions in computational hardware 3. Improvements in computational software 4. The emergence of new data science methods. With the increasing popularity of social networks, online services discovered the unlimited potential for monetization to be unlocked through (a) developing new products and (b) having greater information and data insights than their competitors. Big companies started to form teams of people responsible for analyzing collected data.

• Mykola Lavrskyi
• Apr 23, 2019
• 6 min